Evidence map›Paper›PMID 40751897›Full record

ReviewLa Radiologia medica2025

Advances in renal cancer: diagnosis, treatment, and emerging technologies.

Tsukasa Saida, Mami Iima, Rintaro Ito, Daiju Ueda, Kentaro Nishioka, Ryo Kurokawa, Mariko Kawamura, Kenji Hirata, Maya Honda, Koji Takumi and 8 more

Abstract readReview
PubMed Publisher
In one paragraph

Review in La Radiologia medica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Tsukasa SaidaDepartment of Radiology, Institute of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan. saida_sasaki_tsukasa@md.tsukuba.ac.jp.ORCID http://orcid.org/0000-0003-4530-7375
Mami IimaDepartment of Fundamental Development for Advanced Low Invasive Diagnostic Imaging, Nagoya University Graduate School of Medicine, 65 Tsurumai-Cho, Showa-Ku, Nagoya, Aichi, 466-8550, Japan.
Rintaro ItoDepartment of Radiology, Nagoya University Graduate School of Medicine, 65 Tsurumai-Cho, Showa-Ku, Nagoya, Aichi, 466-8550, Japan.
Daiju UedaDepartment of Artifcial Intelligence, Graduate School of Medicine, Osaka Metropolitan University, 1-4-3 Asahi-Machi, Abeno-Ku, Osaka, 545-8585, Japan.
Kentaro NishiokaRadiation Oncology Division, Global Center for Biomedical Science and Engineering, Faculty of Medicine, Hokkaido University, Nishi 7, Kita 15, Kita-Ku, Sapporo, Hokkaido, 060-8638, Japan.
Ryo KurokawaDepartment of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-Ku, Tokyo, 113-8655, Japan.
Mariko KawamuraDepartment of Radiology, Nagoya University Graduate School of Medicine, 65 Tsurumai-Cho, Showa-Ku, Nagoya, Aichi, 466-8550, Japan.
Kenji HirataDepartment of Diagnostic Imaging, Faculty of Medicine, Hokkaido University, Nishi 7, Kita 15, Kita-Ku, Sapporo, Hokkaido, 060-8638, Japan.
Maya HondaDepartment of Diagnostic Radiology, Kansai Electric Power Hospital, 2-1-7, Fukushima, Fukushima-Ku, Osaka, 553-0003, Japan.
Koji TakumiDepartment of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8520, Japan.
Satoru IdeDepartment of Radiology, University of Occupational and Environmental Health, 1-1 Iseigaoka, Yahatanishi-Ku, Kitakyushu, 807-8555, Japan.
Shunsuke SugawaraDepartment of Diagnostic Radiology, National Cancer Center Hospital, 5-1-1, Tsukiji,Chuo-Ku, Tokyo, 104-0045, Japan.
Tadashi WatabeDepartment of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.
Akihiko SakataDepartment of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Shogoin Kawahara-Cho, Sakyo-Ku, Kyoto, 606-8507, Japan.
Masahiro YanagawaDepartment of Radiology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.
Keitaro SofueDepartment of Radiology, Kobe University Graduate School of Medicine, 7-5-2, Kusunoki-Cho, Chuo-Ku, Kobe, 650-0017, Japan.
Seitaro OdaDepartment of Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University, 1-1-1 Honjo, Chuo-Ku, Kumamoto, 860-8556, Japan.
Shinji NaganawaDepartment of Radiology, Nagoya University Graduate School of Medicine, 65 Tsurumai-Cho, Showa-Ku, Nagoya, Aichi, 466-8550, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review provides a comprehensive overview of current practices and recent advancements in the diagnosis and treatment of renal cancer. It introduces updates in histological classification and explains the imaging characteristics of each tumour based on these changes. The review highlights state-of-the-art imaging modalities, including magnetic resonance imaging, computed tomography, positron emission tomography, and ultrasound, emphasising their crucial role in tumour characterisation and optimising treatment planning. Emerging technologies, such as radiomics and artificial intelligence, are also discussed for their transformative impact on enhancing diagnostic precision, prognostic prediction, and personalised patient management. Furthermore, the review explores current treatment options, including minimally invasive techniques such as cryoablation, radiofrequency ablation, and stereotactic body radiation therapy, as well as systemic therapies such as immune checkpoint inhibitors and targeted therapies.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsHumansRadiosurgeryArtificial intelligenceComputed tomography, positron emission tomographyKidneyMagnetic resonance imagingWHO 2022

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.